Nonnegative periodic dynamics of delayed Cohen-Grossberg neural networks with discontinuous activations

被引：16
|
作者：
He, Xiangnan [1 ]
Lu, Wenlian [1 ]
Chen, Tianping [1 ]
机构：
[1] Fudan Univ, Sch Math, Shanghai Key Lab Contemporary Appl Math, Key Lab Nonlinear Sci,Chinese Minist Educ, Shanghai 200433, Peoples R China
来源：
NEUROCOMPUTING | 2010年 / 73卷 / 13-15期
关键词：
Nonnegative periodic solution; Cohen-Grossberg neural networks; Discontinuous activation; Differential inclusions; GLOBAL EXPONENTIAL STABILITY; PATTERN-FORMATION; ABSOLUTE STABILITY; TIME; BEHAVIORS; SYSTEMS;
D O I：
10.1016/j.neucom.2010.04.006
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we study the nonnegative periodic dynamics of the delayed Cohen-Grossberg neural networks with discontinuous activation functions and periodic interconnection coefficients, self-inhibitions, and external inputs. Filippov theory is utilized to study the viability, namely, the existence of the solution of the Cauchy problem. Under some conditions, the existence and the asymptotical stability of a periodic solution are derived. Numerical examples are provided to illustrate the theoretical results. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：2765 / 2772
页数：8
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